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title: Valkey · Caching up with the Community: Deep Dive with...
description: Percona&#x27;s Kyle Davis, General Manager of the Redis and Valkey Ecosystem, discusses how Valkey is typically deployed alongside relational databases like MySQL...
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og:description: Percona&#x27;s Kyle Davis, General Manager of the Redis and Valkey Ecosystem, discusses how Valkey is typically deployed alongside relational databases like MySQL...
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# Valkey · Caching up with the Community: Deep Dive with Percona’s Kyle Davis

**[Valkey](https://daily.dev/sources/valkey-blog)** · 4 min read · 0 upvotes · 0 comments

## Summary

Percona's Kyle Davis, General Manager of the Redis and Valkey Ecosystem, discusses how Valkey is typically deployed alongside relational databases like MySQL and PostgreSQL as an in-memory caching layer rather than replacing them. He explains Valkey's appeal through its native data structures, which reduce object-relational impedance mismatch, and describes production use cases including real-time fraud detection and IoT telemetry buffering. The conversation highlights Valkey 9.1's memory footprint optimizations and new database-level ACLs, which build on Valkey 9.0's logical database namespaces to enable role-based, per-database access permissions for safer multi-tenant consolidation.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://valkey.io/blog/percona-spotlight>

## Questions this post answers

### What new security feature does Valkey 9.1 add for multi-tenant deployments?

Valkey 9.1 introduces database-level Access Control Lists (ACLs), allowing role-based permissions to be scoped to specific logical databases within a cluster. This builds on Valkey 9.0's logical database namespaces, so a user can be restricted to querying only logical database 0 while another user is limited to database 10, replacing the prior all-or-nothing access model.

_Teams consolidating multi-tenant workloads can track Valkey security updates like this on daily.dev._

### How does Valkey typically get used alongside MySQL or PostgreSQL?

Valkey is deployed almost exclusively as an in-memory caching companion to relational databases like MySQL, Postgres, or MongoDB rather than as a standalone database. Placing it as a caching layer offloads high-concurrency lookup patterns, reducing latency and deferring or eliminating the need for expensive vertical scaling of the primary relational database.

_Developers weighing caching layer architectures can follow Valkey deployment patterns via daily.dev._

### What memory efficiency improvements does Valkey 9.1 provide over previous versions?

Valkey 9.1 delivers a purely software-driven reduction in memory footprint through continuous byte-level and memory-layout optimizations to internal structures. Because Valkey operations run fully in-memory and are constrained by memory capacity rather than CPU, a simple binary upgrade to 9.1 reclaims physical memory on existing infrastructure without requiring any code rewrites.

_Infrastructure teams planning capacity can watch for memory-saving releases like this on daily.dev._

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---

Tags: [#backend](https://daily.dev/tags/backend), [#redis](https://daily.dev/tags/redis), [#valkey](https://daily.dev/tags/valkey)

[View this post on daily.dev](https://daily.dev/posts/valkey-caching-up-with-the-community-deep-dive-with-percona-s-kyle-davis-pmxxkodjy)

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